Towards Learning Analytics for Student Evaluation in the Metaversity

The Metaversity is a general term describing the emerging extended reality environments universities use for teaching and learning in the metaverse. Combining virtual reality technologies and academic content, the Metaversity generates a unique level of detail on students’ data, which contains not only their actions within the virtual learning environment but also their biometrics while engaging in the Metaversity. This major change in scope and volume of data, challenges learning analytics (LA) to design new performance measures to support creating, operating, and managing learning and teaching in the Metaversity. Within these LA challenges, we focus on student evaluation in the Metaversity. Our approach is based on the Theory of Constraints (TOC) thinking process, which defines the system’s goal, and derives all further actions accordingly. Therefore, this research-in-progress suggests a four-level evaluation model for measuring student achievements while performing academic tasks in the Metaversity, or afterward (external assessment; traditional assessment within the VR; experience assessment within the VR; aggregated assessment within the VR). We use a Geology course to demonstrate our student evaluation framework.